Job Overview
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Job Description
Who We Are
Artefact is a French consulting and engineering firm specializing in data and AI, and a leader in Europe. Headquartered in Paris, we are now present in 23 countries across all continents, with a team of 1,700 employees.
Our mission is to help businesses unlock the full potential of AI and data by developing tailor-made solutions that address their specific industry challenges. As pioneers in this field, we combine technological expertise with operational excellence, working alongside the world's leading market players. Our clients span all key economic sectors - industry, retail, luxury, consumer goods, healthcare, and finance - and include major international corporations.
The Data Analytics Team
You will join our Data Analytics Chapter, a team of 60 professionals with expertise across dashboarding, analytics engineering, marketing measurement, and low-code data science. We are one of three technical teams at Artefact (alongside Software Engineering and Data Science), forming a tech community of 160 people. Despite working on different client engagements, we maintain a strong culture of knowledge sharing through dedicated communities of practice. We are growing fast, with the ambition to double our team size over the next five years.
Key Responsibilities of a Data Analytics Manager
As a Data Analytics Manager, your role will encompass:
- Deliver the highest standards of quality on Data marketing projects
- Pilot multidisciplinary teams (consultants, data scientists, data analysts, software engineers, media traders)
- Develop robust, industry-leading measurement and analytics projects that enable clients with visibility across physical and digital customer journeys (online and offline)
- Planning, leading and delivering advanced analytics strategy and solutions for clients including e-commerce, 3rd party tool implementations, and advanced modeling.
- Identify and support the delivery of suitable statistical data analysis techniques, to provide recommendations for clients which exceed performance expectations and maximizes ROI
- Explore automation techniques that create efficiencies and improve ROI (both internally and for clients) such as scripting, tool development or better client reporting methods
- Act as an internal consultant on analytics for significant projects, helping other teams to shape the very best solutions
- Lead through the ‘pitch ownership’ and by taking an ‘analytics lead’ role on new business pitches
Data Marketing and Analytics Leadership
- Lead data analytics development, defining and communicating a clear strategy for the team and the value it will add to the agency
- Work together with the data consultants to champion analytics development and associated platforms on three fronts – internally to the agency, externally to clients and to represent Artefact’s position to the wider marketing community
- Lead and develop roadmaps for our analytics offering, process, and techniques and develop best practice documentation
- Develop review and sign off processes to ensure analytics work is always of the highest possible quality
- Responsible for Artefact being known as exceptional in analytics in the wider market. Actively seek to build Artefact’s profile within the digital marketing community.
Qualifications: Education & Experience Required
Core Requirements:
- 5+ years of hands-on experience in a data-driven environment.
- Strong expertise in at least one of the following domains: Dashboarding & Data Visualization (Power BI, Looker, Tableau, or Superset), Analytics Engineering (dbt, with experience on BigQuery, Snowflake, or Databricks), Marketing Analytics & Measurement (CDP platforms like Treasure Data, Hightouch, Tealium; MMM, attribution, clean rooms), or Low-Code / No-Code Data Science (Dataiku, Copilot Studio, or similar platforms).
- Solid foundation in SQL and Python.
- Familiarity with Git and software engineering fundamentals (versioning, testing, code quality).
- Experience working in cloud environments (GCP, Azure, or AWS).
Nice to Have
- Experience with generative AI applied to analytics (MCP for BI, conversational data interfaces), exposure to multiple domains above, knowledge of statistics and machine learning fundamentals.
Beyond technical expertise, we value: intellectual curiosity, pragmatism and creativity, ability to bridge business and technical teams, autonomy and reliability, and clear communication to build client trust.
Our Recruitment Process
- HR call
- Technical Interview
- Use Case Interview
- Fit Interview
At Artefact, we recruit our employees only on the basis of our needs and the individual qualities of each candidate. We ensure the development of their professional skills and responsibilities without discrimination of any kind, including belief, gender, age, disability, ethnic origin, sexual orientation, membership of a political organization, religion, trade union or minority group.
Key skills/competency
- Data Analytics
- Project Management
- Client Solutions
- Marketing Measurement
- Team Leadership
- Advanced Analytics Strategy
- Data Visualization
- SQL & Python
- Cloud Platforms (GCP, Azure, AWS)
- Generative AI (exposure)
How to Get Hired at Artefact
- Research Artefact's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor, focusing on their AI and data specialization.
- Tailor your resume: Highlight experience in data analytics, team leadership, and client delivery, using keywords like SQL, Python, Power BI, dbt, and marketing measurement relevant to Artefact's projects.
- Showcase your analytics expertise: Prepare to discuss your strongest domain expertise (dashboarding, analytics engineering, or marketing measurement) with practical examples.
- Understand Artefact's client focus: Demonstrate how your skills can solve complex industry challenges for top-tier clients, bridging business and technical needs.
- Prepare for a structured process: Be ready for the HR, technical, use case, and fit interviews by practicing problem-solving and articulating your project contributions clearly.
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